Simulation-based validation of activity logger data for animal behavior studies (original) (raw)
Related papers
The deployment of an ever-evolving array of animal-borne telemetry and data logging 16 devices is rapidly increasing our understanding of the movement, behaviour and 17 physiology of a variety species and the complex, and often highly dynamic, 18 environments they use and respond to. The rapid rate at which new technologies, 19 improvements to current technologies and new analytical techniques are being 20 developed has meant that movements, behaviour and physiological processes are 21 being quantified at finer spatial and temporal scales than ever before. The Fourth 22
ETHOM: event-recording computer software for the study of animal behavior
Accuracy of data capturing is important for the study of animal behavior. ETHOM is a software package which makes the acquisition of the exact behavioral sequence and timing easy. In addition, a useful data analysis subroutine is also included. In the "Recording Data" function, the user can record behavior directly in the field by setting the time interval through the audio alarm function for time sampling of behavioral data. If the behavior is recorded on videotape, this program can also match its timing with the timing recorded on the videotape or the VCR counter, and the user can correct data directly or press a special key to perform editing functions corresponding to the VCR, including pause for timing, different playback speeds, and modifying previous records. Users can also continue recording data from previously saved data in the "Loading Data" function. Two methods of recording are provided, by pressing one key to input (GET-KEY method) or typing a string of keystrokes representing a behavior pattern as desired then pressing the ENTER key (KEY-IN method). The "Analyzing Data" function shows the duration and frequency of each behavior pattern, and the output file of the frequency contingency table. All saved files are in ASCII format and can be read by most commercial word processors and statistics programs. The "Information Analysis and Data Combination" function provides the values of parameters in information theory and allows file combination with "Contingency File", "Result Output File" or "Observational Data File". The program can be executed on any IBM-compatible computer.
Bio-logging: recording the ecophysiology and behaviour of animals moving freely in their environment
2012
Ecological sciences deal with the way organisms interact with one another and their environment. Using sensors to measure various physical and biological characteristics has been a common activity since long ago. However the advent of more accurate technologies and increasing computing capacities demand a better combination of information collected by sensors on multiple spatial, temporal and biological scales.
Observing the unwatchable through acceleration logging of animal behavior
Animal Biotelemetry, 2013
Behavior is an important mechanism of evolution and it is paid for through energy expenditure. Nevertheless, field biologists can rarely observe animals for more than a fraction of their daily activities and attempts to quantify behavior for modeling ecological processes often exclude cryptic yet important behavioral events. Over the past few years, an explosion of research on remote monitoring of animal behavior using acceleration sensors has smashed the decades-old limits of observational studies. Animal-attached accelerometers measure the change in velocity of the body over time and can quantify fine-scale movements and body postures unlimited by visibility, observer bias, or the scale of space use. Pioneered more than a decade ago, application of accelerometers as a remote monitoring tool has recently surged thanks to the development of more accessible hardware and software. It has been applied to more than 120 species of animals to date. Accelerometer measurements are typically collected in three dimensions of movement at very high resolution (>10 Hz), and have so far been applied towards two main objectives. First, the patterns of accelerometer waveforms can be used to deduce specific behaviors through animal movement and body posture. Second, the variation in accelerometer waveform measurements has been shown to correlate with energy expenditure, opening up a suite of scientific questions in species notoriously difficult to observe in the wild. To date, studies of wild aquatic species outnumber wild terrestrial species and analyses of social behaviors are particularly few in number. Researchers of domestic and captive species also tend to report methodology more thoroughly than those studying species in the wild. There are substantial challenges to getting the most out of accelerometers, including validation, calibration, and the management and analysis of large quantities of data. In this review, we illustrate how accelerometers work, provide an overview of the ecological questions that have employed accelerometry, and highlight the emerging best practices for data acquisition and analysis. This tool offers a level of detail in behavioral studies of free-ranging wild animals that has previously been impossible to achieve and, across scientific disciplines, it improves understanding of the role of behavioral mechanisms in ecological and evolutionary processes.
An activity-data-logger for monitoring free-ranging animals
Applied Animal Behaviour Science, 1996
A small (16 cm X 15 cm X 21 cm) solar powered activity-data-logger (ADL) has been developed as a suitable instrument for recording the presence and movements of free-ranging animals. Locomotor activity is recorded by a passive infrared detector (PID). At fixed intervals the signals picked up by the PID are condensed automatically and stored in the ADL. This database can be transferred for further use onto a lap-top or PC. The ADL can store information for up to 80 days and thereafter this information has to be tranferred in order to use the ADL further. A solar-generated accumulator serves as the power supply.
A benchmark for computational analysis of animal behavior, using animal-borne tags
arXiv (Cornell University), 2023
Animal-borne sensors ('bio-loggers') can record a suite of kinematic and environmental data, which can elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are useful for interpreting the large amounts of data recorded by bio-loggers, but there exists no standard for comparing the different machine learning techniques in this domain. To address this, we present the Bio-logger Ethogram Benchmark (BEBE), a collection of datasets with behavioral annotations, standardized modeling tasks, and evaluation metrics. BEBE is to date the largest, most taxonomically diverse, publicly available benchmark of this type, and includes 1654 hours of data collected from 149 individuals across nine taxa. We evaluate the performance of ten different machine
RESEARCH ARTICLE The Use of Acceleration to Code for Animal Behaviours; A Case Study in Free-Ranging
2016
Recent technological innovations have led to the development of miniature, accelerometer-containing electronic loggers which can be attached to free-living animals. Accelerometers provide information on both body posture and dynamism which can be used as descriptors to define behaviour. We deployed tri-axial accelerometer loggers on 12 free-ranging Eur-asian beavers Castor fiber in the county of Telemark, Norway, and on four captive beavers (two Eurasian beavers and two North American beavers C. canadensis) to corroborate acceleration signals with observed behaviours. By using random forests for classifying behavioural patterns of beavers from accelerometry data, we were able to distinguish seven behaviours; standing, walking, swimming, feeding, grooming, diving and sleeping. We show how to apply the use of acceleration to determine behaviour, and emphasise the ease with which this non-invasive method can be implemented. Furthermore, we discuss the strengths and weaknesses of this, ...
2020
Background: Animals respond to environmental variation by changing their movement in a multifaceted way. Recent advancements in biologging increasingly allow for detailed measurements of the multifaceted nature of movement, from descriptors of animal movement trajectories (e.g., using GPS) to descriptors of body part movements (e.g., using tri-axial accelerometers). Because this multivariate richness of movement data complicates inference on the environmental contribution to animal movement, studies generally use simplified movement descriptors in statistical analyses. However, doing so limits the inference on the environmental contribution to movement, as this requires that the multivariate richness of movement data can be fully considered in an analysis. Methods: We propose a data-driven analytic framework to quantify the environmental contribution to animal movement that can accommodate the multifaceted nature of animal movement. Instead of fitting the response of a simplified mo...
ezTrack: An open-source video analysis pipeline for the investigation of animal behavior
2019
Tracking small animal behavior by video is one of the most common tasks in the fields of neuroscience and psychology. Although commercial software exists for the execution of this task, this software often presents enormous cost to the researcher, and can also entail purchasing specific hardware setups that are not only expensive but lack adaptability. Moreover, the inaccessibility of the code underlying this software renders them inflexible. Alternatively, available open source options frequently require extensive model training and can be challenging for those inexperienced with programming. Here we present an open source and platform independent set of behavior analysis pipelines using interactive Python (iPython/Jupyter Notebook) that researchers with no prior programming experience can use. Two modules are described. One module can be used for the positional analysis of an individual animal across a session (i.e., location tracking), amenable to a wide range of behavioral tasks...